docstr: Calculates world_points and img_points.
  
  Since cam_points will have shape (B, N, 3), repeated_intrinsics should have shape (B, N, 3, 3) so that
  kornia.geometry.project_points can be used.
docstr_tok: ["Calculates","world_points","and","img_points",".","Since","cam_points","will","have","shape","(","B",",","N",",","3",")",",","repeated_intrinsics","should","have","shape","(","B",",","N",",","3",",","3",")","so","that","kornia.geometry.project_points","can","be","used","."]
code: def _get_world_points_and_img_points(
      cam_points, world_to_cam_4x4, repeated_intrinsics
  ):
      r"""Calculates world_points and img_points.
  
      Since cam_points will have shape (B, N, 3), repeated_intrinsics should have shape (B, N, 3, 3) so that
      kornia.geometry.project_points can be used.
      """
      cam_to_world_4x4 = kornia.geometry.inverse_transformation(
          world_to_cam_4x4
      )
      world_points = kornia.geometry.transform_points(
          cam_to_world_4x4, cam_points
      )
      img_points = kornia.geometry.project_points(
          cam_points, repeated_intrinsics
      )
  
      return world_points, img_points
  
file_path: kornia/test/geometry/calibration/test_pnp.py
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  from kornia.geometry.calibration.pnp import _mean_isotropic_scale_normalize
  from kornia.testing import assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 3 for calling the TestSolvePnpDlt obj's underlying member method code with example usage: obj._get_world_points_and_img_points(cam_points, world_to_cam_4x4, repeated_intrinsics) and returns: world_points,  img_points